def create_dataset(
self,
config: Optional[Dict[str, Any]] = None,
inject_fake_data: bool = True,
patch_checks: Optional[bool] = None,
**kwargs: Any,
) -> Iterator[Tuple[torchvision.datasets.VisionDataset, Dict[str, Any]]]:
r"""Create the dataset in a temporary directory.
The configuration passed to the dataset is populated to contain at least all parameters with default values.
For this the following order of precedence is used:
1. Parameters in :attr:`kwargs`.
2. Configuration in :attr:`config`.
3. Configuration in :attr:`~DatasetTestCase.DEFAULT_CONFIG`.
4. Default parameters of the dataset.
Args:
config (Optional[Dict[str, Any]]): Configuration that will be used to create the dataset.
inject_fake_data (bool): If ``True`` (default) inject the fake data with :meth:`.inject_fake_data` before
creating the dataset.
patch_checks (Optional[bool]): If ``True`` disable integrity check logic while creating the dataset. If
omitted defaults to the same value as ``inject_fake_data``.
**kwargs (Any): Additional parameters passed to the dataset. These parameters take precedence in case they
overlap with ``config``.
Yields:
dataset (torchvision.dataset.VisionDataset): Dataset.
info (Dict[str, Any]): Additional information about the injected fake data. See :meth:`.inject_fake_data`
for details.
"""
if patch_checks is None:
patch_checks = inject_fake_data
special_kwargs, other_kwargs = self._split_kwargs(kwargs)
complete_config = self._KWARG_DEFAULTS.copy()
if self.DEFAULT_CONFIG:
complete_config.update(self.DEFAULT_CONFIG)
if config:
complete_config.update(config)
if other_kwargs:
complete_config.update(other_kwargs)
if "download" in self._HAS_SPECIAL_KWARG and special_kwargs.get("download", False):
# override download param to False param if its default is truthy
special_kwargs["download"] = False
patchers = self._patch_download_extract()
if patch_checks:
patchers.update(self._patch_checks())
with get_tmp_dir() as tmpdir:
args = self.dataset_args(tmpdir, complete_config)
info = self._inject_fake_data(tmpdir, complete_config) if inject_fake_data else None
with self._maybe_apply_patches(patchers), disable_console_output():
dataset = self.DATASET_CLASS(*args, **complete_config, **special_kwargs)
yield dataset, info
def create_dataset(
self,
config: Optional[Dict[str, Any]] = None,
inject_fake_data: bool = True,
patch_checks: Optional[bool] = None,
**kwargs: Any,
) -> Iterator[Tuple[torchvision.datasets.VisionDataset, Dict[str, Any]]]:
r"""Create the dataset in a temporary directory.
Args:
config (Optional[Dict[str, Any]]): Configuration that will be used to create the dataset. If omitted, the
default configuration is used.
inject_fake_data (bool): If ``True`` (default) inject the fake data with :meth:`.inject_fake_data` before
creating the dataset.
patch_checks (Optional[bool]): If ``True`` disable integrity check logic while creating the dataset. If
omitted defaults to the same value as ``inject_fake_data``.
**kwargs (Any): Additional parameters passed to the dataset. These parameters take precedence in case they
overlap with ``config``.
Yields:
dataset (torchvision.dataset.VisionDataset): Dataset.
info (Dict[str, Any]): Additional information about the injected fake data. See :meth:`.inject_fake_data`
for details.
"""
default_config = self._DEFAULT_CONFIG.copy()
if config is not None:
default_config.update(config)
config = default_config
if patch_checks is None:
patch_checks = inject_fake_data
special_kwargs, other_kwargs = self._split_kwargs(kwargs)
if "download" in self._HAS_SPECIAL_KWARG:
special_kwargs["download"] = False
config.update(other_kwargs)
patchers = self._patch_download_extract()
if patch_checks:
patchers.update(self._patch_checks())
with get_tmp_dir() as tmpdir:
args = self.dataset_args(tmpdir, config)
info = self._inject_fake_data(tmpdir,
config) if inject_fake_data else None
with self._maybe_apply_patches(patchers), disable_console_output():
dataset = self.DATASET_CLASS(*args, **config, **special_kwargs)
yield dataset, info
def create_dataset(
self,
config: Optional[Dict[str, Any]] = None,
inject_fake_data: bool = True,
disable_download_extract: Optional[bool] = None,
**kwargs: Any,
) -> Iterator[Tuple[torchvision.datasets.VisionDataset, Dict[str, Any]]]:
r"""Create the dataset in a temporary directory.
Args:
config (Optional[Dict[str, Any]]): Configuration that will be used to create the dataset. If omitted, the
default configuration is used.
inject_fake_data (bool): If ``True`` (default) inject the fake data with :meth:`.inject_fake_data` before
creating the dataset.
disable_download_extract (Optional[bool]): If ``True`` disable download and extract logic while creating
the dataset. If ``None`` (default) this takes the same value as ``inject_fake_data``.
**kwargs (Any): Additional parameters passed to the dataset. These parameters take precedence in case they
overlap with ``config``.
Yields:
dataset (torchvision.dataset.VisionDataset): Dataset.
info (Dict[str, Any]): Additional information about the injected fake data. See :meth:`.inject_fake_data`
for details.
"""
if config is None:
config = self.CONFIGS[0].copy()
special_kwargs, other_kwargs = self._split_kwargs(kwargs)
config.update(other_kwargs)
if disable_download_extract is None:
disable_download_extract = inject_fake_data
with get_tmp_dir() as tmpdir:
output = self.inject_fake_data(
tmpdir, config) if inject_fake_data else None
if output is None:
raise UsageError(
"The method 'inject_fake_data' needs to return at least an integer indicating the number of "
"examples for the current configuration.")
if isinstance(output,
collections.abc.Sequence) and len(output) == 2:
args, info = output
else:
args = (tmpdir, )
info = output
if isinstance(info, int):
info = dict(num_examples=info)
elif isinstance(info, dict):
if "num_examples" not in info:
raise UsageError(
"The information dictionary returned by the method 'inject_fake_data' must contain a "
"'num_examples' field that holds the number of examples for the current configuration."
)
else:
raise UsageError(
f"The additional information returned by the method 'inject_fake_data' must be either an integer "
f"indicating the number of examples for the current configuration or a dictionary with the the "
f"same content. Got {type(info)} instead.")
cm = self._disable_download_extract if disable_download_extract else nullcontext
with cm(special_kwargs), disable_console_output():
dataset = self.DATASET_CLASS(*args, **config, **special_kwargs)
yield dataset, info